In every professional field, statistical analysis of data is crucial since it enables professionals to be responsible for their acts. According to Venezian, Nye and Hofflander (1999), statistical analysis acts as a tool for measuring authenticity and liability of professional claims. For this reason, the tool highly influences how decisions are made and also enhances the implementation of public policies.
Evidence has shown that statistical analysis of data is widely used in the medical profession by psychologists especially when applying certain public policies. From a careful review of literature, many psychologists have done further research to credit the current research hypothesis (Venezian, Nye & Hofflander, 1999). By so doing, it makes it possible to establish new policies based on the data collected.
Nevertheless, in spite of in-depth research activities and assumptions, policies formulated ought to have professional liability (Venezian, Nye & Hofflander, 1999). Some of the policies can be competent or incompetent. Therefore, this calls for action to be taken in order to merit them. In this case, statistical review of data helps professionals to identify and implement policies that are appropriate and suitable to the public without infringing the rights of individuals irrespective of personal differences.
In line with this, my opinion is that statistical analyses play a vital role to support public policy decision making. For instance, criminal prosecution is one of the major issues that require statistical analysis since data presented is used to ensure that effective decisions are made and right policies applied (Venezian, Nye & Hofflander, 1999).
Most of the criminal laws have been formulated on the merit of inferences derived from diverse incidences and are geared towards enhancing professional liability among lawyers. To some extent, some of the inferences can be biased and hence decisions and formulated policies can contravene the rights of victims.
In most cases, some of the disciplinary polices governing criminal prosecution have the likelihood of bringing hostility and can result into social imbalance (Venezian, Nye & Hofflander, 1999). Therefore, a statistical review helps to weigh the benefits of policies and decisions made from the available data in order to foster social balance in society.
Additionally, whenever policies are formulated from non-reviewed data, there is likelihood of causing problems in future due to previous malpractices (Venezian, Nye & Hofflander, 1999). Therefore, disciplined psychologists should conduct a statistical review on data at hand to eliminate bias.
The latter enables them to make effective decisions which influence policy making. It is imperative to note that malpractices have negative effects since they lead to wrong decisions made on public policies (Venezian, Nye & Hofflander, 1999).
Another crucial factor to note is that incidences related to crime are very diverse. For example, murder is a criminal offence but it can occur under different contexts. In this case, there are individuals who commit the offence deliberately for the sake of revenge while others do it for self defense. These two cases cannot be valued on similar dimensions.
Apparently, the two cases should be considered independently and appropriate polices applied to ensure that justice prevails. Therefore, it becomes tricky to apply existing polices to the emerging events (Venezian, Nye & Hofflander, 1999). In this case, it is recommended that every case should be handled independently such that data collected is thoroughly reviewed.
To recap it all, statistical analysis of data is essential since it helps professionals to examine the liability of data collected. Additionally, it assists in formulating efficient decisions that govern implementation of public policies. Data review also helps to control professional malpractices that result from biased data.
Reference
Venezian, E., Nye, F. & Hofflander, A. E. (1999). The distribution of claims for professional malpractice: Some statistical and public policy aspects. Journal of Risk and Insurance 56(4), 686-687.